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11 Jul 2026 Job Information Organisation/Company CNRS Department Institut d'Electronique de Microélectronique et de Nanotechnologie Research Field Physics Researcher Profile First Stage Researcher (R1) Application Deadline 31 Jul 2026 - 23:59 (UTC) Country France Type of Contract Temporary Job...
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complexity, from a single droplet to the semi-industrial scale. The work will identify the influence of temperature and water content on reaction kinetics and then build and validate multi-response kinetic
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field) and ground-based (radio) data - Use of various software codes: (i) radio emission simulation code, (ii) solar wind propagation code. - Development of software (preferably in Python) for data
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modeling and optimization methods for the management of multi-energy platforms integrating electricity and heat systems within. The research aims at characterizing and valorizing the flexibility potential
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reconfigurable multi-source microgrids - Collaboration and co-supervision : LAAS-CNRS & AMPERE – - French Program France2030 PEPR FutuRE Context and challenges: Electrical grids are evolving towards decentralized
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project, which aims to use interglacial and millennial-scale climate changes of the last 220,000 years as natural experiments to provide the first integrated understanding of atmosphere-land-ocean
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capable of automatically selecting the simulation strategy best suited to a given prediction objective, while optimizing the trade-off between accuracy and computational cost. The work will build on multi
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built around a multi-scale logic: the assembly of phases, inclusions, porosity, and diffuse microcracking must first be linked to measurable macroscopic properties, and these macroscopic descriptors must
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uncertainties can affect the effectiveness of emergency response operations. The objective is to develop a multi-agent model of emergency response operations during flash floods, in order to study how the use
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: automating information extraction from unstructured data, proposing a common representation of multi-source data, developing data fusion and knowledge enrichment methods, automatically detecting anomalies, and